Oxide-Lab
Modern desktop application (Rust + Tauri v2 + Svelte 5 + Candle (HF)) for communicating with AI models that runs completely locally on your computer. No subscriptions, no data sent to the internet — just you and your personal AI assistant
Stars: 103
Oxide Lab is a private AI chat desktop application with local LLM support, allowing users to run large language models locally without internet connectivity or external API services. Built with Rust and Tauri v2, it offers a fast and secure chat interface where all inference happens on the user's machine, ensuring data privacy and security. The application supports multiple architectures, model formats, and hardware accelerations, along with streaming text generation and a modern UI built with Svelte and Tailwind CSS.
README:
Private AI chat desktop application with local LLM support.
All inference happens on your machine — no cloud, no data sharing.
- What is this?
- Demo
- Key Features
- Installation & Setup
- How to Start Using
- System Requirements
- Supported Models
- Privacy and Security
- Acknowledgments
- License
Oxide Lab is a native desktop application for running large language models locally. Built with Rust and Tauri v2, it provides a fast, private chat interface without requiring internet connectivity or external API services.
https://github.com/user-attachments/assets/0b9c8ff9-7793-4108-8b62-b0800cbd855e
https://github.com/user-attachments/assets/27c1f544-69e0-4a91-8fa5-4c21d67cb7c7
https://github.com/user-attachments/assets/ce5337d5-3e63-4263-b6a7-56e6847bbc71
- 100% local inference — your data never leaves your machine
- Multi-architecture support: Llama, Qwen2, Qwen2.5, Qwen3, Qwen3 MoE, Mistral, Mixtral, DeepSeek, Yi, SmolLM2
- GGUF and SafeTensors model formats
- Hardware acceleration: CPU, CUDA (NVIDIA), Metal (Apple Silicon), Intel MKL, Apple Accelerate
- Streaming text generation
- Multi-language UI: English, Russian, Brazilian Portuguese
- Modern interface built with Svelte 5 and Tailwind CSS
- Node.js (for frontend build)
- Rust toolchain (for backend)
- For CUDA: NVIDIA GPU with CUDA toolkit
- For Metal: macOS with Apple Silicon
# Install dependencies
npm install
# Run with CPU backend
npm run tauri:dev:cpu
# Run with CUDA backend (NVIDIA GPU)
npm run tauri:dev:cuda
# Platform-aware development
npm run app:dev# Build with CPU backend
npm run tauri:build:cpu
# Build with CUDA backend
npm run tauri:build:cudanpm run lint # ESLint
npm run lint:fix # ESLint with auto-fix
npm run check # Svelte type checking
npm run format # Prettier formatting
npm run test # Vitest testscargo clippy # Linting
cargo test # Unit tests
cargo audit # Security audit- Build or download the application
- Download a compatible GGUF or SafeTensors model (e.g., from Hugging Face)
- Launch Oxide Lab
- Load your model through the interface
- Start chatting
- Windows, macOS, or Linux
- Minimum 4 GB RAM (8+ GB recommended for larger models)
- For GPU acceleration:
- NVIDIA: CUDA-compatible GPU
- Apple: M1/M2/M3 chip (Metal)
Architectures with full support:
- Llama (1, 2, 3), Mistral, Mixtral, DeepSeek, Yi, SmolLM2, CodeLlama
- Qwen2/2.5, Qwen2.5/2 MoE
- Qwen3, Qwen3 MoE
Formats:
- GGUF (quantized models)
- SafeTensors
- All processing happens locally on your device
- No telemetry or data collection
- No internet connection required for inference
- Content Security Policy (CSP) enforced
This project is built on top of excellent open-source work:
- Candle — ML framework for Rust (HuggingFace)
- Tauri — Desktop application framework
- Svelte — Frontend framework
- Tokenizers — Fast tokenization (HuggingFace)
See THIRD_PARTY_LICENSES.md for full dependency attribution.
Apache-2.0 — see LICENSE
Copyright (c) 2025 FerrisMind
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